Transformer-based acoustic modeling for hybrid speech recognition Y Wang, A Mohamed, D Le, C Liu, A Xiao, J Mahadeokar, H Huang, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 243 | 2020 |
Transformer-transducer: End-to-end speech recognition with self-attention CF Yeh, J Mahadeokar, K Kalgaonkar, Y Wang, D Le, M Jain, K Schubert, ... arXiv preprint arXiv:1910.12977, 2019 | 164 | 2019 |
Emformer: Efficient memory transformer based acoustic model for low latency streaming speech recognition Y Shi, Y Wang, C Wu, CF Yeh, J Chan, F Zhang, D Le, M Seltzer ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 159 | 2021 |
Emotion recognition from spontaneous speech using hidden markov models with deep belief networks D Le, EM Provost 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 216-221, 2013 | 131 | 2013 |
Discretized Continuous Speech Emotion Recognition with Multi-Task Deep Recurrent Neural Network. D Le, Z Aldeneh, EM Provost Interspeech, 1108-1112, 2017 | 83 | 2017 |
Deep shallow fusion for RNN-T personalization D Le, G Keren, J Chan, J Mahadeokar, C Fuegen, ML Seltzer 2021 IEEE Spoken Language Technology Workshop (SLT), 251-257, 2021 | 70 | 2021 |
Contextualized streaming end-to-end speech recognition with trie-based deep biasing and shallow fusion D Le, M Jain, G Keren, S Kim, Y Shi, J Mahadeokar, J Chan, ... arXiv preprint arXiv:2104.02194, 2021 | 69 | 2021 |
Alignment restricted streaming recurrent neural network transducer J Mahadeokar, Y Shangguan, D Le, G Keren, H Su, T Le, CF Yeh, ... 2021 IEEE Spoken Language Technology Workshop (SLT), 52-59, 2021 | 66 | 2021 |
From senones to chenones: Tied context-dependent graphemes for hybrid speech recognition D Le, X Zhang, W Zheng, C Fügen, G Zweig, ML Seltzer 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2019 | 65 | 2019 |
Automatic quantitative analysis of spontaneous aphasic speech D Le, K Licata, EM Provost Speech Communication 100, 1-12, 2018 | 57 | 2018 |
Classification of huntington disease using acoustic and lexical features M Perez, W Jin, D Le, N Carlozzi, P Dayalu, A Roberts, EM Provost Interspeech 2018, 1898, 2018 | 57 | 2018 |
Automatic assessment of speech intelligibility for individuals with aphasia D Le, K Licata, C Persad, EM Provost IEEE/ACM transactions on audio, speech, and language processing 24 (11 …, 2016 | 57 | 2016 |
Improving RNN transducer based ASR with auxiliary tasks C Liu, F Zhang, D Le, S Kim, Y Saraf, G Zweig 2021 IEEE Spoken Language Technology Workshop (SLT), 172-179, 2021 | 44 | 2021 |
Improving Automatic Recognition of Aphasic Speech with AphasiaBank. D Le, EM Provost Interspeech, 2681-2685, 2016 | 41 | 2016 |
Weak-attention suppression for transformer based speech recognition Y Shi, Y Wang, C Wu, C Fuegen, F Zhang, D Le, CF Yeh, ML Seltzer arXiv preprint arXiv:2005.09137, 2020 | 28 | 2020 |
Automatic Paraphasia Detection from Aphasic Speech: A Preliminary Study. D Le, K Licata, EM Provost Interspeech, 294-298, 2017 | 28 | 2017 |
Stop: A dataset for spoken task oriented semantic parsing P Tomasello, A Shrivastava, D Lazar, PC Hsu, D Le, A Sagar, A Elkahky, ... 2022 IEEE Spoken Language Technology Workshop (SLT), 991-998, 2023 | 26 | 2023 |
Modeling pronunciation, rhythm, and intonation for automatic assessment of speech quality in aphasia rehabilitation D Le, EM Provost Fifteenth Annual Conference of the International Speech Communication …, 2014 | 26 | 2014 |
Improved neural language model fusion for streaming recurrent neural network transducer S Kim, Y Shangguan, J Mahadeokar, A Bruguier, C Fuegen, ML Seltzer, ... ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 24 | 2021 |
Dissecting user-perceived latency of on-device E2E speech recognition Y Shangguan, R Prabhavalkar, H Su, J Mahadeokar, Y Shi, J Zhou, C Wu, ... arXiv preprint arXiv:2104.02207, 2021 | 24 | 2021 |